Stochastic Local Search

1st Edition

Foundations and Applications

Authors: Holger H. Hoos Thomas Stützle
Print ISBN: 9781493303731
eBook ISBN: 9780080498249
Imprint: Morgan Kaufmann
Published Date: 16th September 2004
Page Count: 658
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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics.

Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool.

Key Features

  • Provides the first unified view of the field
  • Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications
  • Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms
  • A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms


Academic and industry researchers in CS, AI, operations research, and engineering (as an introduction to and/or overview of the field or as a reference text); practitioners who need to solve combinatorial problems for practical applications

Table of Contents

Prologue Part I. Foundations

  1. Introduction
  2. SLS Methods
  3. Generalized Local Search Machines
  4. Empirical Analysis of SLS Algorithms
  5. Search Space Structure and SLS Performance Part II. Applications
  6. SAT and Constraint Satisfaction
  7. MAX-SAT and MAX-CSP
  8. Traveling Salesman Problems
  9. Scheduling Problems
  10. Other Combinatorial Problems Epilogue Glossary


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© Morgan Kaufmann 2005
Morgan Kaufmann
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About the Author

Holger H. Hoos

Affiliations and Expertise

The University of British Columbia, Canada

Thomas Stützle

Affiliations and Expertise

Darmstadt University of Technology, Germany


“The book and companion web page are well written, easy to read and suited for students, scholars, researchers and practitioners alike. We see SLS:FA as an important step towards an improved understanding of SLS methods and their behavior, and we expect that this book will inspire future researchers and spark new lines of work in this area." --Ruben Ruiz and Marco Pranzo, European Journal of Operational Research Article in Press

"Hoos and Stützle, two major players in the field, provide us with an excellent overview of stochastic local search. If you are looking for a book that covers all the major metaheuristics, gives you insight into their working, and guides you in their application to a wide set of combinatorial optimization problems, this is the book. " --Marco Dorigo, Université Libre de Bruxelles

"Stochastic Local Search: Foundations and Applications provides an original and synthetic presentation of a large class of algorithms more commonly known as metaheuristics. Over the last 20 years, these methods have become extremely popular, often representing the only practical approach for tackling so many of the hard combinatorial problems that are encountered in real-life applications. Hoos and Stützle’s treatment of the topic is comprehensive and covers a variety of techniques, including simulated annealing, tabu search, genetic algorithms and ant colony optimization, but a main feature of the book is its proposal of a most welcome unifying framework for describing and analyzing the various methods." --Michel Gendreau, Université de Montréal

"Local search algorithms are often the most practical approach to solving constraint satisfaction and optimization problems that admit no fast deterministic solution. This book is full of information and insights that would be invaluable for both researchers and practitioners." --Henry Kautz, University of Washington